Remote Data Engineer

Summary

Join Endpoint as a Data Engineer to design, implement, and maintain data infrastructure that drives business intelligence, analytics, and data science initiatives. The ideal candidate will have expertise in Databricks, SQL, Python, Spark, and other Big Data tools.

Requirements

• Bachelor's degree in Computer Science, Software Engineering, Mathematics, or a related technical field is preferred
• 4-6 years of technical experience with a strong focus on Big Data technologies in any of these areas: software engineering, integrations, data warehousing, data analysis, business intelligence, preferably at a technology or biotech/pharma company
• Proficiency in Databricks for data engineering tasks
• Advanced knowledge of SQL for complex queries, data manipulation, and performance tuning
• Strong programming skills in Python for scripting and automation
• Experience with Big Data tools (e.g., Spark, Hadoop) and data processing frameworks
• Familiarity with BI tools (e.g., Tableau, Power BI) and experience in developing dashboards and reports
• Experience with cloud platforms & tools like Azure ADF or Databricks
• Familiarity with data modeling and data architecture design
• Understanding of machine learning concepts and their application in data engineering

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines using Databricks and other big data technologies
• Optimize data workflows to handle large volumes of data efficiently
• Build and manage data warehouses and data lakes to store structured and unstructured data
• Utilize SQL, Python, Spark for data extraction, transformation, and loading (ETL) processes
• Work closely with data analysts and data scientists to understand their data needs and ensure the availability of clean, reliable data
• Integrate data from various sources, ensuring consistency and accuracy across the data ecosystem
• Implement data quality checks to ensure data accuracy, completeness, and consistency
• Develop and enforce data governance policies and procedures to maintain high data quality standards
• Develop and support BI tools and dashboards, providing business insights and data-driven decision-making support
• Work with stakeholders to understand reporting requirements and deliver actionable insights
• Automate repetitive data processing tasks to improve efficiency and reduce manual work
• Continuously monitor and improve data pipeline performance, addressing bottlenecks and optimizing resources
• Document data processes, workflows, and architecture for future reference and knowledge sharing
• Ensure compliance with data security and privacy regulations, such as GDPR, HIPAA, etc

Benefits

• Medical
• Dental
• Vision
• Life
• STD/LTD
• 401(K)
• Paid time off (PTO) or Flexible time off (FTO)
• Company bonus where applicable